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ViaAlgo’s Assign AI: increase efficiency service-wide

Written by Via Transportation | Jul 29, 2022 4:00:00 AM

Meet ViaAlgo, the brain behind Via's 500 worldwide deployments. In our ViaAlgo Features Series, get to know her expertise, honed by delivering millions of rides all over the globe.

If ViaAlgo’s Routing Engine makes the decisions regarding linking requested trips and generates directions from pickups to drop-offs, her Assign AI features optimize these assignments so that they fit within the driver shifts that are available for assignment. Assign AI has two main actions: Optimize All and Auto-Reassign. In addition to ViaAlgo's automated tools, dispatchers always have access to algo-assisted and purely manual assignment and reassignment feature. 

Agency staff use “Optimize All” to generate the best possible Ride Plan that can be delivered by the available fleet. They can run "Optimize All" the night before service, after all trip requests have been received, or in the middle of a service day to re-optimize the entire plan based on new conditions or information. 

Staff can see a preview of how well the Ride Plan has accommodated requested rides: in this case, 110 requests have been “assigned,” and 2 have remained “unassigned.” When the number of unassigned requests is small, dispatchers can use a variety of “Assign” tools (see “Unassigned Rides”) to resolve them directly in the Ride Plan. A large number may indicate that the agency should try to secure additional supply for the following day, and re-run “Optimize All” with additional shifts available. Over time, “Optimize All” can inform supply planning in addition to creating an effective Ride Plan. 

On the day of service, ViaAlgo continuously runs the Auto-Reassign function in the background of the Ride Plan. Auto-Reassign looks for places in the Ride Plan that it can adjust to optimize for efficiency and on-time performance — all while staying within agency rules. If a shift is added, a ride is canceled, or a driver is running late, Auto-Reassign can subtly readjust the Ride Plan to best fit the new circumstances.